class_docstr: Distributes sequence embeddings to be data-parallel.
class_docstr_tok: ["Distributes","sequence","embeddings","to","be","data-parallel","."]
code: def __init__(self) -> None:
      super().__init__()
  
file_path: torchrec/torchrec/distributed/sharding/dp_sequence_sharding.py
imports: from typing import Any, Dict, Optional
  import torch
  from torchrec.distributed.embedding_lookup import GroupedEmbeddingsLookup
  from torchrec.distributed.embedding_sharding import BaseEmbeddingDist, BaseEmbeddingLookup, BaseSparseFeaturesDist
  from torchrec.distributed.embedding_types import BaseGroupedFeatureProcessor
  from torchrec.distributed.sharding.dp_sharding import BaseDpEmbeddingSharding, DpSparseFeaturesDist
  from torchrec.distributed.sharding.sequence_sharding import SequenceShardingContext
  from torchrec.distributed.types import Awaitable, NoWait
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 1 to create a new DpSequenceEmbeddingDist object from inherited base classes: BaseEmbeddingDist with example: obj = DpSequenceEmbeddingDist()